Yeah, I have a very large sample size, about 60,000 observations. Multicollinearity should not be a problem here. The weird thing is that SPSS can converge very quickly and gives out reasonable results. The only problem I can think of is that, my first level (random) variables are dummy variables: 6 housing types, and I used five dummies in model and one as the reference. I also tried to combine them into two groups and use only dummy at random level, but it does not work either.
is there any one here has similar experience with the LME function in R? Thanks. Harry On Tue, Aug 4, 2009 at 1:28 AM, ONKELINX, Thierry <thierry.onkel...@inbo.be>wrote: > Dear Harry, > > Your model seems rather complex. Do you have enough data to support it? > Did you check for multicollinearity between the variables? > > HTH, > > Thierry > > > > ------------------------------------------------------------------------ > ---- > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature > and Forest > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, > methodology and quality assurance > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > tel. + 32 54/436 185 > thierry.onkel...@inbo.be > www.inbo.be > > To call in the statistician after the experiment is done may be no more > than asking him to perform a post-mortem examination: he may be able to > say what the experiment died of. > ~ Sir Ronald Aylmer Fisher > > The plural of anecdote is not data. > ~ Roger Brinner > > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of > data. > ~ John Tukey > > -----Oorspronkelijk bericht----- > Van: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > Namens Hongwei Dong > Verzonden: maandag 3 augustus 2009 19:45 > Aan: r-help@r-project.org > Onderwerp: Re: [R] lme funcion in R > > Thanks for the replies above. Here are my script and data structure: > library(nlme) > tlevel<-lme(fixed = LN_unitlandval ~ > MH_D+APT_D+ResOth_D+NonRes_D+Vacant_D+access_emp1+pct_vacant+transit_D+p > ark_dum,data=lusdrdata,random > = ~MH_D+APT_D+ResOth_D+NonRes_D+Vacant_D | TAZ) > > str: > > $ TAZ : int 100 100 100 100 100 100 100 100 100 100 ... > $ MH_D : num 0 0 0 0 0 0 0 0 0 0 ... > $ APT_D : num 0 0 0 0 0 0 0 0 0 0 ... $ ResOth_D : num 0 0 0 0 0 0 0 0 0 > 0 ... $ NonRes_D : num 0 0 0 0 0 0 0 0 0 1 ... > $ Vacant_D : num 1 1 1 0 0 1 1 1 1 0 ... > $ access_emp1 : num 45.8 45.8 45.8 45.8 45.8 ... > $ pct_vacant : num 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 ... $ > transit_D : > num 0 0 0 0 0 0 0 0 0 0 ... $ park_dum : num 0 0 0 0 0 0 0 0 0 0 ... > > > Thanks. > > Harry > > > > On Mon, Aug 3, 2009 at 10:36 AM, Jason Morgan <jwm-r-h...@skepsi.net> > wrote: > > > On 2009.08.03 10:15:46, Hongwei Dong wrote: > > > Hi, R users, > > > I'm using the "lme" function in R to estimate a 2 level mixed > > > effects model, in which the size of the subject groups are > > > different. It turned > > out > > > that It takes forever for R to converge. I also tried the same thing > > > > in > > SPSS > > > and SPSS can give the results out within 20 minutes. Anyone can give > > > > me > > some > > > advice on the lme function in R, especially why R does not converge? > > Thanks. > > > > > > Harry > > > > Hello Harry, > > > > As Chuck mentions, providing some more information on the model and > > the data you are using would be helpful. Also, be sure to compare the > > optimization methods used in SPSS to that used in R. You can change > > the optimization method in R if the default seems to be causing > > issues. See help(lmeControl) for numerous setting options. > > > > ~Jason > > > > -- > > Jason W. Morgan > > Graduate Student > > Department of Political Science > > *The Ohio State University* > > 154 North Oval Mall > > Columbus, Ohio 43210 > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver > weer > en binden het INBO onder geen enkel beding, zolang dit bericht niet > bevestigd is > door een geldig ondertekend document. The views expressed in this message > and any annex are purely those of the writer and may not be regarded as > stating > an official position of INBO, as long as the message is not confirmed by a > duly > signed document. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
